1. Field of the Invention
The present invention relates to a channel equalizing method and channel equalizer in a digital communication system.
2. Description of the Related Art
Channel equalization is a signal processing technique typically used in a digital communication system. Channel equalization is typically performed in a digital communication system in order to prevent the occurrence of channel noise, channel distortion, multi-path error and multi-user interference, thereby improving system performance. Channel equalizers may typically be found in household appliances such as digital TVs and personal communication systems. The use of a variety of different types of channel equalizers in household appliances such as described above may increase a carrier interference to noise ratio, known as a signal-to-noise ratio (SNR) and reduce a symbol error rate (SER) of an input signal.
The Advanced Television Systems Committee (ATSC) provides standards for digital high-definition television (HDTV). The ATSC document A53, dated Sep. 16, 1995 describes an approved standard for digital TV. This standard specifies specific training sequences that are incorporated into video signals transmitted over a terrestrial broadcast, cable and/or satellite channel, etc.
ATSC document A54, dated Oct. 4, 1995, describes general implementation of this standard. ATSC document A54 discloses a method of adapting on equalizer's filter response of an equalizer to adequately compensate for channel distortion. This method may be disadvantageous, however, in that there is a higher probability that coefficients which are set in the equalizer are not set so as to adequately compensate for channel distortion which may be present as the equalizer first operates (i.e., upon start-up or initialization of the equalizer).
To force a convergence of the equalizer coefficients, a well-known ‘original training sequence’ is transmitted. An error signal is formed by subtracting a locally generated copy of the training sequence from the output of the equalizer. The coefficients are set so as to minimize the error signal. After adaptation of the equalizer with the training signal, the equalizer may be used for filtering a video signal, for example.
In general, linear filters are used for channel equalization. Feedback-type non-linear filters are also commonly used in order to effectively remove impulse noise and non-linear distortion present in a communication channel, so as to improve equalizer performance. Further, a least mean square algorithm, which has a simple structure and requires a small amount of calculation, may be used as a ‘tap coefficient updating algorithm’ in the equalizer. However, coefficients typically converge slowly when using the least mean square algorithm, which means the convergence time increases. Thus, this algorithm is typically unsuitable for a multi-path communication environment, in which the speed of data transmissions, and transmission delays, are increased. Accordingly, an equalizer is required which is capable of converging coefficients as fast as possible, during a short duration such as a period of a training signal, for example.
A ‘Kalman algorithm’ is one of a group of algorithms having fast converging characteristics. However, the Kalman algorithm requires a substantial amount of calculation, thus there are difficulties in applying this algorithm to a communication system. Although substantial advances in hardware have enabled the use of the Kalman algorithm in digital communication systems, the increased processing power needed for these substantial calculations is a problem to be addressed.